Ubuntu-certified workstations from Dell and HP with NVIDIA, microk8s and Kubeflow

Accelerate data science

Lightest footprint

Laptop to workstation

GPGPU optional

Develop and test AI

/Bare metal AI

Kubernetes on bare metal with NVIDIA GPGPU acceleration

Highest performance

On-premise with local data

Hardware recommendations

Fully managed options

/Google Cloud AI

GKE on Ubuntu with NVIDIA GPGPU acceleration

Effectively infinite scale

Portable workloads

Fastest cloud ML

/Canonical Cloud AI

Kubeflow on Kubernetes on Openstack with NVIDIA GPGPU acceleration

Maximize benefits of OpenStack

On-premise with local data

Hardware recommendations

Fully managed options

Kubeflow features

Kubeflow brings together all the most popular tools for machine learning, starting with JupyterHub and Tensorflow, in a standardised workflow running on Kubernetes. Optimised on a wide range of hardware and cloud infrastructure, Kubeflow lets your data scientists focus on the pieces that matter to the business.

It is an extensible framework, which allows you to leverage the tools of your choice. Start with Tensorflow and JupyterHub or bring your own frameworks and tools. Combined with Kubeflow’s automation, this will accelerate your machine learning activities — from model development to model training to model sharing.

Install Kubeflow

Initiated by Google on Ubuntu for perfect portability of AI workloads from your workstation, to your data center rack on Canonical’s bare metal k8s or Canonical’s OpenStack virtualization, to Google’s Cloud Kubernetes service GKE which also runs on Ubuntu. Simple.

Canonical’s Kubeflow and Kubernetes on bare metal servers, with NVIDIA GPGPUs, provides an ultra high-performance machine learning cluster. Deployment, support, and optional remote management and remote operations make it the best way to accelerate your data science and machine learning.

AI add-on for Kubernetes Discoverer and Discoverer Plus

AI/ML Add-on

/month

Workshop

One additional day on Kubeflow, including Tensorflow and JupyterHub, covering everything your business needs to know to have a full on-prem/off-prem AI/ML game plan.

Workshop

Canonical will leverage its network of data science partners to deliver an AI assessment as part of the workshop with options for ongoing engagement post-deployment.

Understand AI lifecycle

Preliminary AI discovery

Development assessment

Deploy and operate analysis

Finalize initial AI strategy

IoT and Edge AI

Train in the cloud. Act at the edge.

Cameras, music systems, cars, even firewalls and CPE are becoming smarter. From natural language processing to image recognition, from real-time high-speed autonomous navigation to network intrusion detection. Ubuntu gives you a seamless operational framework for development, training and inference all the way out to the edge.